In image processing, exposure fusion combines multiple exposures of the same scene into an output image. The multiple exposures can collectively capture the scene with a higher dynamic range than a camera is capable of capturing with a single exposure. This allows a higher quality output image which can use pixels from the various input images while avoiding those that are overexposed and underexposed. In some instances, a user may wish to edit the output image, such as to increase or decrease the brightness of the output image. Various conventional brightness adjustment algorithms could be applied to the output image to accomplish this task.
Adjusting image brightness of an output image from exposure fusion will often result in color distortion in the adjusted image. For example, many brightness adjustment algorithms assume a linear relationship between pixel color values of an image and sensor data. This linear relationship is disrupted by exposure fusion because color values of the output image are determined from multiple exposures. Thus, when adjusting an output image from exposure fusion, some pixel color values may quickly exceed their cutoff value (maximum or minimum value), resulting in color distortion. Complex algorithms could attempt to account for the non-linearity of the pixel color values. However, these algorithms are processor intensive and would still amplify any color distortion that may already exist in the output image.